Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hezi, Shi"'
Publikováno v:
Computer Aided Design 2023
This paper addresses the challenges of designing mesh convolution neural networks for 3D mesh dense prediction. While deep learning has achieved remarkable success in image dense prediction tasks, directly applying or extending these methods to irreg
Externí odkaz:
http://arxiv.org/abs/2408.13762
Publikováno v:
Computer-Aided Design. 162:103550
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74cdbad506a72d41f055362e61371046
https://doi.org/10.1016/j.cad.2023.103550
https://doi.org/10.1016/j.cad.2023.103550
Autor:
Li Wang, Ruifeng Li, Hezi Shi, Jingwen Sun, Lijun Zhao, Hock Soon Seah, Chee Kwang Quah, Budianto Tandianus
Publikováno v:
Sensors, Vol 19, Iss 4, p 893 (2019)
Environmental perception is a vital feature for service robots when working in an indoor environment for a long time. The general 3D reconstruction is a low-level geometric information description that cannot convey semantics. In contrast, higher lev
Externí odkaz:
https://doaj.org/article/72c28be309254f188e788f86def25715
Publikováno v:
ROBIO
In order to achieve an intuitive interaction and visual semantic navigation for the indoor robot, we propose a novel object-aware hybrid map. The existing map is usually a metric map, lacking semantics for interaction. We combine objects in the indoo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72c18c1655554f22e07e8cbc52f54c76
https://doi.org/10.1109/robio49542.2019.8961495
https://doi.org/10.1109/robio49542.2019.8961495